COMPRESSING SOURCE CODE WRITTEN IN A SCRIPTING LANGUAGE

    公开(公告)号:WO2011109252A3

    公开(公告)日:2011-09-09

    申请号:PCT/US2011/026360

    申请日:2011-02-25

    Abstract: A method described herein includes at a computing device, receiving, over a network connection, a data packet from an external source, wherein the data packet comprises a compressed abstract syntax tree (AST)-based representation of source code written in a scripting language. The method further includes decompressing the compressed AST-based representation of the source code to generate a decompressed AST. The method also includes causing at least one processor on the computing device to execute at least one instruction represented in the decompressed AST subsequent to the compressed AST-based representation of the source code being decompressed.

    FORMATTING DATA BY EXAMPLE
    2.
    发明申请
    FORMATTING DATA BY EXAMPLE 审中-公开
    按示例格式化数据

    公开(公告)号:WO2012103159A2

    公开(公告)日:2012-08-02

    申请号:PCT/US2012/022454

    申请日:2012-01-24

    CPC classification number: G06F17/211

    Abstract: Data formatting rules to convert data from one form to another form are automatically determined based on a user's edits. A machine learning heuristic is applied to a user's edits to determine a data formatting rule that may be applied to data. For example, a user may make edits that add/remove characters from data, concatenate data, extract data, rename data, and the like. The machine learning heuristic may be automatically triggered in response to an event (e.g. after a predetermined number of edits are made to a same type of data) or manually triggered (e.g. selecting a user interface option). The data formatting rule may be applied to other data and the results of the formatting reviewable by the user. Based on further edits/reviews, the data formatting rule may be updated. The data formatting rules may be stored for later use.

    Abstract translation:

    根据用户的编辑自动确定将数据从一种表单转换为另一种表单的数据格式规则。 机器学习启发式应用于用户的编辑以确定可应用于数据的数据格式化规则。 例如,用户可以进行编辑,从数据添加/删除字符,连接数据,提取数据,重命名数据等。 机器学习启发式可以响应于事件(例如,在对相同类型的数据进行预定次数的编辑之后)或手动触发(例如,选择用户界面选项)而自动触发。 数据格式化规则可以应用于其他数据以及用户可查看的格式化结果。 基于进一步的编辑/评论,数据格式化规则可以被更新。 数据格式化规则可以被存储以供以后使用。

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